Enginsoft

An advanced and efficient way to model and forecast drainage network impact

React & Typescript
GraphQL
NodeJS
Leaflet Custom Implementation
Docker
Kubernetes
Custom Babel

Planning for housing growth requires a huge amount of modelling in order to anticipate the changing growth scenarios – so how can water companies quickly and effectively understand the impact of housing growth without the need to turn to modelling for every change in growth

Utilise the latest AI tech to capture the response of a drainage network so that any growth scenario can be ‘dallied-in’ along with the impact instantly reported and visualised on the catchment

Using a custom babel plugin written for this project models are transpiled into a form that can easily be consumed by NodeJS in order to have an efficient web experience allowing users to alter input and output parameters and see results in near real-time to model and predict water patterns to make for better city planning in the future.

Finally, a React frontend with custom Leaflet map implementation to bring it all to life on a single screen allowing for multiple parameters to be altered.

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